VLDB 2026 Research / reviewers in the wild / expert
Reese Butterfuss
dblp:259/2812
· DBLP profile ↗
6ranked-venue papers
1as first author
5since 2021 · last 2023
0000-0001-9326-4176ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 5 · 1 first-author · 4 since 2021Human-computer interaction and ubiquitous computing · 3 · 3 since 2021Artificial intelligence and machine learning · 2 · 1 first-author · 1 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | iSTART: Adaptive Comprehension Strategy Training and Stealth Literacy AssessmentabstractThe Interactive Strategy Training for Active Reading and Thinking (iSTART) game-based intelligent tutoring system (ITS) was developed with a foundation of comprehension theory and principles of learning science to improve students’ comprehension of complex scientific texts. iSTART has been shown to improve reading comprehension for learners from middle school through adulthood, particularly lower knowledge readers, through strategy instruction and game-based practice. This paper describes iSTART, the theoretical foundations that have guided iSTART development, and evidence for the feasibility of game-based practice to improve learning outcomes. This paper also introduces a novel method of assessing students’ reading comprehension through game-based literacy assessments that have been incorporated in iSTART. The development of these stealth assessments was guided by recent work emphasizing the need for rapid, dynamic, and low stakes assessments that evaluate students’ reading skills in the context of brief, dynamic games. Stealth assessments can generate estimates of multiple aspects of students’ reading comprehension quickly and within a motivating environment. The work described in this paper is a promising method to assess students’ literacy in an unobtrusive and authentic way that may lead to improved learning outcomes for students. Danielle S. McNamara, Tracy Arner, Reese Butterfuss, Micah Watanabe, Natalie Newton, Kathryn S. McCarthy, Laura K. Allen, Rod D. Roscoe |
Int. J. Hum. Comput. Interact. | 3 |
| 2022 | Using Markov Models and Random Walks to Examine Strategy Use of More or Less Successful Comprehenders
Katerina Christhilf, Natalie Newton, Reese Butterfuss, Kathryn S. McCarthy, Laura K. Allen, Joseph Magliano, Danielle S. McNamara |
EDM | 3 |
| 2022 | Integrating Speech Technology into the iSTART-Early Intelligent Tutoring System
Renu Balyan, Tracy Arner, Ellen Orcutt, Reese Butterfuss, Panayiota Kendeou, Danielle S. McNamara |
ITS | 5 |
| 2022 | iSTART-Early: Interactive Strategy Training for Early Readers
Panayiota Kendeou, Ellen Orcutt, Tracy Arner, Renu Balyan, Reese Butterfuss, Micah Watanabe, Danielle S. McNamara |
ITS | 6 |
| 2021 | Social Media Spillover: Attitude-Inconsistent Tweets Reduce Memory for Subsequent Information
Reese Butterfuss, Tracy Arner, Laura K. Allen, Danielle S. McNamara |
CogSci | 1 |
| 2020 | Epistemic Beliefs, Language, and Sources: Interactive Effects on Belief and Trust of Scientific Information
Rina Harsch, Reese Butterfuss, Panayiota Kendeou |
CogSci | 2 |